Amelia Hardy


Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agent
Ethan A. Chi | Ashwin Paranjape | Abigail See | Caleb Chiam | Trenton Chang | Kathleen Kenealy | Swee Kiat Lim | Amelia Hardy | Chetanya Rastogi | Haojun Li | Alexander Iyabor | Yutong He | Hari Sowrirajan | Peng Qi | Kaushik Ram Sadagopan | Nguyet Minh Phu | Dilara Soylu | Jillian Tang | Avanika Narayan | Giovanni Campagna | Christopher Manning
Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue

We present Chirpy Cardinal, an open-domain social chatbot. Aiming to be both informative and conversational, our bot chats with users in an authentic, emotionally intelligent way. By integrating controlled neural generation with scaffolded, hand-written dialogue, we let both the user and bot take turns driving the conversation, producing an engaging and socially fluent experience. Deployed in the fourth iteration of the Alexa Prize Socialbot Grand Challenge, Chirpy Cardinal handled thousands of conversations per day, placing second out of nine bots with an average user rating of 3.58/5.


Effective Social Chatbot Strategies for Increasing User Initiative
Amelia Hardy | Ashwin Paranjape | Christopher Manning
Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue

Many existing chatbots do not effectively support mixed initiative, forcing their users to either respond passively or lead constantly. We seek to improve this experience by introducing new mechanisms to encourage user initiative in social chatbot conversations. Since user initiative in this setting is distinct from initiative in human-human or task-oriented dialogue, we first propose a new definition that accounts for the unique behaviors users take in this context. Drawing from linguistics, we propose three mechanisms to promote user initiative: back-channeling, personal disclosure, and replacing questions with statements. We show that simple automatic metrics of utterance length, number of noun phrases, and diversity of user responses correlate with human judgement of initiative. Finally, we use these metrics to suggest that these strategies do result in statistically significant increases in user initiative, where frequent, but not excessive, back-channeling is the most effective strategy.